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Record W4388953246 · doi:10.5455/jjee.204-1688997421

Design and Simulation of a Floating Solar Photovoltaic System for an Offshore Aquaculture Site in Canada

2023· article· en· W4388953246 on OpenAlexaboutno aff
Nadeem Asgher, Tariq Iqbal

Bibliographic record

VenueJordan Journal of Electrical Engineering · 2023
Typearticle
Languageen
FieldEnergy
TopicHybrid Renewable Energy Systems
Canadian institutionsnot available
Fundersnot available
KeywordsCost of electricity by sourcePhotovoltaic systemRenewable energyEnvironmental scienceElectric power systemSolar energyEngineeringElectricity generationMarine engineeringAutomotive engineeringEnvironmental economicsPower (physics)Electrical engineering

Abstract

fetched live from OpenAlex

This article presents the design and commercial feasibility of a floating solar photovoltaic (FSPV) power system for an offshore fish farm site located in the Newfoundland province of Canada. The offshore fish farms are energy-intensive units, and the fish feeding system is the primary energy consumer. Due to the remote location, the grid/utility power infrastructure does not exist, and diesel generators fulfill energy needs, which is expensive and detrimental to the environment. A FSPV power system is proposed as a replacement for the fossil fuel energy source. A comprehensive study is conducted to investigate the actual energy requirements of a site and an appropriate hybrid solar system is designed using Homer Pro software. The designed system’s techno-commercial feasibility is evaluated based on three different scenarios (base, ideal and worst). The obtained results show that the renewable energy penetration for all cases is very convincing and encouraging. The Levelized Cost of Energy (LCOE) computed by the software for all three cases is compared with the existing setup produced energy cost. It reveals that the designed FSPV produces significantly economical power. Overall, the outcomes of this investigation demonstrate the potential of FSPV systems as a viable and sustainable solution for powering fish farms and contributing to the sustainability of the aquaculture industry.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.097
Threshold uncertainty score0.963

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.013
GPT teacher head0.217
Teacher spread0.203 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations6
Published2023
Admission routes1
Has abstractyes

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